A statistical analysis of large-scale brightness and velocity fluctuations in the solar atmosphere.
Local large scale brightness and velocity fluctuations in different layers of solar atmosphere analyzed statistically
Appenzeller, I.↗
SEARCH · Search NASA
Results for “statistical analysis”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes
The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.
HAADF-STEM↗
A statistical analysis of the low-energy geosynchronous plasma environment. I - Electrons. II - Ions
Data on the geosynchronous plasma environment between approximately 30 eV and 80 keV are analyzed statistically. Nearly 50 days of 10 minute averages of the first four moments of the distribution function from low-energy plasma detectors on the ATS-5 and ATS-6 geosynchronous satellites were used. The data were studied in terms of occurrence frequency, local time variations, and response to geomagnetic activity. These techniques revealed marked differences in the ATS-5 and ATS-6 data bases. When translated into a 2-Maxwellian representation, it was found that (1) the ATS-6 data covered an energy range not covered by ATS-5 (between 1 and 50 eV) and (2) there was a definite change in the ion plasma between the ATS-5 and ATS-6 measurements. Simple expressions are derived to simulate the relationship between the four moments, and a model is presented, which takes into account the ATS-5 and ATS-6 plasma variations. Despite the differences in the ion data, the accuracy of the four-moment representation was found valid for characterizing the geosynchronous electron population.
Garrett, H. B.↗
Mars 2020 Perseverance Entry Descent and Landing Simulation Statistical Analysis and Operations
On February 18, 2021, the Perseverance rover and Ingenuity helicopter demonstra- tion landed at Jezero Crater. The Entry, Descent, and Landing (EDL) architecture, largely the same used to land Curiosity at Gale Crater on August 6, 2012, required high-fidelity flight dynamics simulation with two independent tools to verify per- formance. The process for creating the EDL simulation using the Dynamics Sim- ulator for Entry, Descent and Surface landing (DSENDS) tool will be discussed, along with its use for for independent verification of the EDL statistical analy- sis results and reference trajectory simulation. Analysis and usage details both in development and cruise, along with post-landing assessment of the prediction performance of the simulation, will also be discussed.
"O'Farrell, Clara"↗
Multivariate statistical analysis software technologies for astrophysical research involving large data bases
The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.
Djorgovski, Stanislav↗
Multivariate statistical analysis software technologies for astrophysical research involving large data bases
The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.
Djorgovski, George↗
Statistical analysis of landing contact conditions for three lifting body research vehicles
The landing contact conditions for the HL-10, M2-F2/F3, and the X-24A lifting body vehicles are analyzed statistically for 81 landings. The landing contact parameters analyzed are true airspeed, peak normal acceleration at the center of gravity, roll angle, and roll velocity. Ground measurement parameters analyzed are lateral and longitudinal distance from intended touchdown, lateral distance from touchdown to full stop, and rollout distance. The results are presented in the form of histograms for frequency distributions and cumulative frequency distribution probability curves with a Pearson Type 3 curve fit for extrapolation purposes.
Larson, R. R.↗
Statistical analysis of several terminal area traffic collision hazard factors.
An 11 hr sample of air traffic, comprising 584 tracks recorded at Atlanta during peak periods of August 1967, is analyzed to examine the statistical characteristics of range-guard intrusions and airspace conflicts in a terminal area. The number of intrusions (of an imaginary 3-naut mile, 500-ft range guard surrounding each aircraft) and number of conflicts (of the projected airspace for two aircraft) for a track exhibit Poisson variations with track duration. The hourly rate of intrusions follows the gas model square-law variation with traffic density, but the hourly conflict rate, contrary to the gas model, decreases with greater traffic density.
Ruetenik, J. R.↗
A statistical analysis of gust-velocity measurements as affected by pilots and airplanes
Explore the source record for details and available documents.
LOADS, GUST↗
Statistical analysis of time transfer data from Timation 2
Between July 1973 and January 1974, three time transfer experiments using the Timation 2 satellite were conducted to measure time differences between the U.S. Naval Observatory and Australia. Statistical tests showed that the results are unaffected by the satellite's position with respect to the sunrise/sunset line or by its closest approach azimuth at the Australian station. Further tests revealed that forward predictions of time scale differences, based on the measurements, can be made with high confidence.
Luck, J. M.↗
Statistical Analysis of a Large Sample Size Pyroshock Test Data Set Including Post Flight Data Assessment
The Earth Observing System (EOS) Terra spacecraft was launched on an Atlas IIAS launch vehicle on its mission to observe planet Earth in late 1999. Prior to launch, the new design of the spacecraft's pyroshock separation system was characterized by a series of 13 separation ground tests. The analysis methods used to evaluate this unusually large amount of shock data will be discussed in this paper, with particular emphasis on population distributions and finding statistically significant families of data, leading to an overall shock separation interface level. The wealth of ground test data also allowed a derivation of a Mission Assurance level for the flight. All of the flight shock measurements were below the EOS Terra Mission Assurance level thus contributing to the overall success of the EOS Terra mission. The effectiveness of the statistical methodology for characterizing the shock interface level and for developing a flight Mission Assurance level from a large sample size of shock data is demonstrated in this paper.
Hughes, William O.↗
Statistical analysis of close pairs of QSOs
The observation of close pairs of QSOs with very different redshifts has been suggested by some as evidence in support of the noncosmological redshift hypothesis. A method is described for determining the statistical significance of such pairs. As an example, it is shown that the statistical significance of the pair 1548+115a,b is not well defined and ranges from approximately 99% confidence to about 60%. If statistical methods are to be used in such cases, they must not be argued a posteriori.
Burbidge, E. M.↗
Near-Real-Time Statistical Analysis and Visualization of Streamflow from a Deep-Learning Rainfall-Runoff Model
Near-real-time (NRT) streamflow data are critical importance for timely water resources management. Here, we developed an open-source tool, FlowStats, for NRT streamflow analysis and visualization in Germany, based on NRT meteorological data from the German Weather Service and simulated streamflow from a long short-term memory neural network (LSTM). The LSTM model achieved very good overall performance, median NSE of 0.80 for the test period across 1,479 catchments. FlowStats provides options for deriving various streamflow statistics, from normal and abnormal streamflow detection to drought and flood analyses. An example analysis from FlowStats revealed widespread below-normal to extreme low-flow conditions across Germany from March to May 2025, which weakened from June to September 2025. Drought analysis for September 2025 highlighted severe to extreme drought conditions in northwestern Germany, while flood classifications indicated that high-flow events occurred in southwestern Germany. FlowStats can be used for various hydrological assessments to support water resources management.
Hydrological modeling↗
Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
Neergaard, Lynn↗
Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
Neergaard, L.↗
Linear statistical analysis of maneuver optimization techniques
It is shown how a method for maneuver design during the Jovian satellite tour phase of the Galileo mission requires a full-scale redesign of the tour at each maneuver. Software was developed to provide insight into the statistical properties of this process; it is based on the use of linear perturbations to provide trajectory propagation and a least squares representation of the optimization. The result is a Monte Carlo program, making it possible to evaluate the proposed strategy.
Maize, Earl H.↗
On intracluster Faraday rotation. II - Statistical analysis
The comparison of a reliable sample of radio source Faraday rotation measurements seen through rich clusters of galaxies, with sources seen through the outer parts of clusters and therefore having little intracluster Faraday rotation, indicates that the distribution of rotation in the former population is broadened, but only at the 80% level of statistical confidence. Employing a physical model for the intracluster medium in which the square root of magnetic field strength/turbulent cell per gas core radius number ratio equals approximately 0.07 microgauss, a Monte Carlo simulation is able to reproduce the observed broadening. An upper-limit analysis figure of less than 0.20 microgauss for the field strength/turbulent cell ratio, combined with lower limits on field strength imposed by limitations on the Compton-scattered flux, shows that intracluster magnetic fields must be tangled on scales greater than about 20 kpc.
Lawler, J. M.↗
Data Analysis & Statistical Methods for Command File Errors
This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.
Correlation Analysis↗